Byte-Sized-Chunks: Graph Algorithms and Problems in Java

Byte-Sized-Chunks: Graph Algorithms and Problems in Java, available at $49.99, has an average rating of 4.65, with 28 lectures, based on 63 reviews, and has 2877 subscribers.

You will learn about Design and implement software using canonical graph algorithms – Djikstra, Prim, Kruskal, Bellman Ford and topological sort Understand the use-cases for the common graph algorithm This course is ideal for individuals who are Nope! Please don't enroll for this class if you have already enrolled for our 15-hour course 'From 0 to 1: Data Structures and Algorithms' or Yep! Computer Science and Engineering grads who are looking to really visualise data structures, and internalise how they work or Yep! Experienced software engineers who are looking to refresh important fundamental concepts or Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role It is particularly useful for Nope! Please don't enroll for this class if you have already enrolled for our 15-hour course 'From 0 to 1: Data Structures and Algorithms' or Yep! Computer Science and Engineering grads who are looking to really visualise data structures, and internalise how they work or Yep! Experienced software engineers who are looking to refresh important fundamental concepts or Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role.

Enroll now: Byte-Sized-Chunks: Graph Algorithms and Problems in Java

Summary

Title: Byte-Sized-Chunks: Graph Algorithms and Problems in Java

Price: $49.99

Average Rating: 4.65

Number of Lectures: 28

Number of Published Lectures: 28

Number of Curriculum Items: 28

Number of Published Curriculum Objects: 28

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Design and implement software using canonical graph algorithms – Djikstra, Prim, Kruskal, Bellman Ford and topological sort
Understand the use-cases for the common graph algorithm

Who Should Attend

Nope! Please don't enroll for this class if you have already enrolled for our 15-hour course 'From 0 to 1: Data Structures and Algorithms'
Yep! Computer Science and Engineering grads who are looking to really visualise data structures, and internalise how they work
Yep! Experienced software engineers who are looking to refresh important fundamental concepts
Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role

Target Audiences

Nope! Please don't enroll for this class if you have already enrolled for our 15-hour course 'From 0 to 1: Data Structures and Algorithms'
Yep! Computer Science and Engineering grads who are looking to really visualise data structures, and internalise how they work
Yep! Experienced software engineers who are looking to refresh important fundamental concepts
Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role

Note: This course is a subset of our much longer course ‘From 0 to 1: Data Structures & Algorithms’ so please don’t sign up for both:-)

This is an animated, visual and spatial way to learn data structures and algorithms

Our brains process different types of information differently – evolutionarily we are wired to absorb information best when it is visual and spatial i.e. when we can close our eyes and see it
More than most other concepts, Data Structures and Algorithms are best learnt visually.These are incredibly easy to learn visually, very hard to understand most other ways
This course has been put together by a team with tons of everyday experience in thinking about these concepts and using them at work at Google, Microsoft and Flipkart

Taught by a Stanford-educated ex-Googler.

The graph is a data structure that is used to model a very large number of real world problems. It’s also an programming interview favorite. The study of graphs and algorithms associated with graphs forms an entire field of study called graph theory.

Directed and undirected graphs
Adjacency matrices, lists and sets
Breadth and Depth-First traversal
Topological sort
Djikstra’s algorithm
Bellman-Ford algorithm
Prim’s algorithm
Kruskal’s algorithm

Course Curriculum

Chapter 1: Its A Connected World!

Lecture 1: You, This Course, and Us!

Lecture 2: Introducing The Graph

Lecture 3: Types Of Graphs

Lecture 4: The Directed And Undirected Graph

Lecture 5: Representing A Graph In Code

Lecture 6: Graph Using An Adjacency Matrix

Lecture 7: Graph Using An Adjacency List And Adjacency Set

Lecture 8: Comparison Of Graph Representations

Lecture 9: Graph Traversal – Depth First And Breadth First

Chapter 2: Graph Algorithms

Lecture 1: Topological Sort In A Graph

Lecture 2: Implementation Of Topological Sort

Chapter 3: Shortest Path Algorithms

Lecture 1: Introduction To Shortest Path In An Unweighted Graph – The Distance Table

Lecture 2: The Shortest Path Algorithm Visualized

Lecture 3: Implementation Of The Shortest Path In An Unweighted Graph

Lecture 4: Introduction To The Weighted Graph

Lecture 5: Shortest Path In A Weighted Graph – A Greedy Algorithm

Lecture 6: Dijkstra's Algorithm Visualized

Lecture 7: Implementation Of Dijkstra's Algorithm

Lecture 8: Introduction To The Bellman Ford Algorithm

Lecture 9: The Bellman Ford Algorithm Visualized

Lecture 10: Dealing With Negative Cycles In The Bellman Ford Algorithm

Lecture 11: Implementation Of The Bellman Ford Algorithm

Chapter 4: Spanning Tree Algorithms

Lecture 1: Prim's Algorithm For a Minimal Spanning Tree

Lecture 2: Use Cases And Implementation Of Prim's Algorithm

Lecture 3: Kruskal's Algorithm For a Minimal Spanning Tree

Lecture 4: Implementation Of Kruskal's Algorithm

Chapter 5: Graph Problems

Lecture 1: Design A Course Schedule Considering Pre-reqs For Courses

Lecture 2: Find The Shortest Path In A Weighted Graphs – Fewer Edges Better

Instructors

Loony Corn
An ex-Google, Stanford and Flipkart team

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 7 votes
4 stars: 17 votes
5 stars: 39 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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